{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/141181"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/141181","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Management and Analysis of Localization Information in Uncrewed Aerial Systems","abstract":"Reliable localization is a critical enabling function for autonomous uncrewed aerial vehicles (UAVs), particularly in environments where Global Navigation Satellite System (GNSS) signals are degraded or unavailable. This thesis investigates how 5G cellular networks - leveraging dense terrestrial infrastructure, precise timing, and recently standardized UAV oriented capabilities - can enhance localization performance, coordination, and mission reliability for both individual UAVs and cooperative swarms. First, we present a release-by-release analysis of 3GPP’s evolving support for UAVs from LTE Release 15 through 5G-Advanced Release 19, highlighting architectural, radio, and sidelink mechanisms that enable identification, 3D tracking, command-and-control, and integration with UAS Traffic Management systems, while also identifying key gaps and opportunities for future enhancements in UAV communication and localization. Second, we design and experimentally validate the first 5G-enabled UAV testbed developed at Wireless@VT, enabling controlled investigation of how communication latency affects swarm behavior. Using this platform, we demonstrate that the primary determinant of swarm responsiveness is the 5G numerology configuration—specifically, how increasing OFDM subcarrier spacing reduces transmission time intervals and air-interface latency. This reduction significantly improves the timeliness of localization-information exchange, enabling tighter formation keeping, faster synchronization, and overall behavior more consistent with the low-latency, high-reliability goals of URLLC-class services. Finally, we develop a localization-driven trajectory optimization framework that incorporates Position Error Bounds derived from the Fisher Information Matrix, enabling UAVs to identify and traverse geometrically favorable routes that reduce localization uncertainty by up to 30% without compromising communication performance. Together, these contributions demonstrate how standardized 5G communication and localization capabilities can practically enhance UAV autonomy and robustness in GNSS-challenged environments.","abstract_html":"Reliable localization is a critical enabling function for autonomous uncrewed aerial vehicles (UAVs), particularly in environments where Global Navigation Satellite System (GNSS) signals are degraded or unavailable. This thesis investigates how 5G cellular networks - leveraging dense terrestrial infrastructure, precise timing, and recently standardized UAV oriented capabilities - can enhance localization performance, coordination, and mission reliability for both individual UAVs and cooperative swarms. First, we present a release-by-release analysis of 3GPP’s evolving support for UAVs from LTE Release 15 through 5G-Advanced Release 19, highlighting architectural, radio, and sidelink mechanisms that enable identification, 3D tracking, command-and-control, and integration with UAS Traffic Management systems, while also identifying key gaps and opportunities for future enhancements in UAV communication and localization. Second, we design and experimentally validate the first 5G-enabled UAV testbed developed at Wireless@VT, enabling controlled investigation of how communication latency affects swarm behavior. Using this platform, we demonstrate that the primary determinant of swarm responsiveness is the 5G numerology configuration—specifically, how increasing OFDM subcarrier spacing reduces transmission time intervals and air-interface latency. This reduction significantly improves the timeliness of localization-information exchange, enabling tighter formation keeping, faster synchronization, and overall behavior more consistent with the low-latency, high-reliability goals of URLLC-class services. Finally, we develop a localization-driven trajectory optimization framework that incorporates Position Error Bounds derived from the Fisher Information Matrix, enabling UAVs to identify and traverse geometrically favorable routes that reduce localization uncertainty by up to 30% without compromising communication performance. Together, these contributions demonstrate how standardized 5G communication and localization capabilities can practically enhance UAV autonomy and robustness in GNSS-challenged environments.","abstract_has_math":false,"creators":["Kumar, Anand Mahesh"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Electrical Engineering","degree_department":"Electrical and Computer Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Reed, Jeffrey H.","Tripathi, Nishith D."],"committee_members":["Buehrer, R. Michael"],"year":2025,"date_issued":"2025-11-24","date_published":"2025-11-24","updated_at":"2026-07-22T22:19:33Z","subjects":["uncrewed aerial vehicles","localization","path planning","3GPP","UAV testbed"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10919/141181","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Reed, Jeffrey H.","Tripathi, Nishith D."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Buehrer, R. 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This thesis investigates how 5G cellular networks - leveraging dense terrestrial infrastructure, precise timing, and recently standardized UAV oriented capabilities - can enhance localization performance, coordination, and mission reliability for both individual UAVs and cooperative swarms. First, we present a release-by-release analysis of 3GPP’s evolving support for UAVs from LTE Release 15 through 5G-Advanced Release 19, highlighting architectural, radio, and sidelink mechanisms that enable identification, 3D tracking, command-and-control, and integration with UAS Traffic Management systems, while also identifying key gaps and opportunities for future enhancements in UAV communication and localization. Second, we design and experimentally validate the first 5G-enabled UAV testbed developed at Wireless@VT, enabling controlled investigation of how communication latency affects swarm behavior. Using this platform, we demonstrate that the primary determinant of swarm responsiveness is the 5G numerology configuration—specifically, how increasing OFDM subcarrier spacing reduces transmission time intervals and air-interface latency. This reduction significantly improves the timeliness of localization-information exchange, enabling tighter formation keeping, faster synchronization, and overall behavior more consistent with the low-latency, high-reliability goals of URLLC-class services. Finally, we develop a localization-driven trajectory optimization framework that incorporates Position Error Bounds derived from the Fisher Information Matrix, enabling UAVs to identify and traverse geometrically favorable routes that reduce localization uncertainty by up to 30% without compromising communication performance. Together, these contributions demonstrate how standardized 5G communication and localization capabilities can practically enhance UAV autonomy and robustness in GNSS-challenged environments."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Drones are becoming increasingly important in areas such as emergency response, infrastructure inspection, agriculture, and delivery services. For these missions to be safe and reliable—especially when drones fly beyond a pilot’s line of sight—they must always know their location accurately. Today, most drones depend on GPS, but GPS signals can be blocked by tall buildings, weakened indoors, or deliberately disrupted. This thesis explores how next-generation 5G cellular networks can help drones maintain accurate location information and operate more safely, even when GPS is unavailable. The first part of this work explains how recent wireless communication standards have added new features specifically designed for drones. These features support drone identification, tracking, safe communication with controllers, and coordination with air-traffic systems. We also highlight several gaps in today’s standards and identify opportunities where future improvements could make drone operations even more reliable. The second part of the thesis introduces the first 5G-enabled drone testbed built at Wireless@ VT. This platform allowed us to study how communication delays affect the ability of multiple drones to fly together as a coordinated group, or “swarm.” Our experiments show that a key factor in improving swarm responsiveness is the way 5G divides its radio channels. By increasing the spacing between these channels—known as the subcarrier spacing—the network can transmit information more quickly, reducing delay and enabling drones to react faster. This behavior closely aligns with the goals of future ultra-reliable, low-latency communication services. Finally, the thesis presents a new way for drones to choose flight paths that improve how accurately they can determine their location using 5G signals. By selecting routes that offer better geometry with respect to nearby cell towers, a drone can significantly reduce its positioning uncertainty without harming its communication performance. Together, these contributions show how 5G networks can enhance the safety, reliability, and autonomy of drone operations, particularly in situations where GPS alone is not enough."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Management and Analysis of Localization Information in Uncrewed Aerial Systems"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Reed, Jeffrey H.","Tripathi, Nishith D."],"dc:contributor.committeemember":["Buehrer, R. Michael"],"dc:contributor.department":["Electrical and Computer Engineering"],"dc:creator":["Kumar, Anand Mahesh"],"dc:date.accessioned":["2026-02-06T13:30:23Z"],"dc:date.available":["2026-02-06T13:30:23Z"],"dc:date.issued":["2025-11-24"],"dc:description.abstract":["Reliable localization is a critical enabling function for autonomous uncrewed aerial vehicles (UAVs), particularly in environments where Global Navigation Satellite System (GNSS) signals are degraded or unavailable. This thesis investigates how 5G cellular networks - leveraging dense terrestrial infrastructure, precise timing, and recently standardized UAV oriented capabilities - can enhance localization performance, coordination, and mission reliability for both individual UAVs and cooperative swarms. First, we present a release-by-release analysis of 3GPP’s evolving support for UAVs from LTE Release 15 through 5G-Advanced Release 19, highlighting architectural, radio, and sidelink mechanisms that enable identification, 3D tracking, command-and-control, and integration with UAS Traffic Management systems, while also identifying key gaps and opportunities for future enhancements in UAV communication and localization. Second, we design and experimentally validate the first 5G-enabled UAV testbed developed at Wireless@VT, enabling controlled investigation of how communication latency affects swarm behavior. Using this platform, we demonstrate that the primary determinant of swarm responsiveness is the 5G numerology configuration—specifically, how increasing OFDM subcarrier spacing reduces transmission time intervals and air-interface latency. This reduction significantly improves the timeliness of localization-information exchange, enabling tighter formation keeping, faster synchronization, and overall behavior more consistent with the low-latency, high-reliability goals of URLLC-class services. Finally, we develop a localization-driven trajectory optimization framework that incorporates Position Error Bounds derived from the Fisher Information Matrix, enabling UAVs to identify and traverse geometrically favorable routes that reduce localization uncertainty by up to 30% without compromising communication performance. Together, these contributions demonstrate how standardized 5G communication and localization capabilities can practically enhance UAV autonomy and robustness in GNSS-challenged environments."],"dc:description.abstractgeneral":["Drones are becoming increasingly important in areas such as emergency response, infrastructure inspection, agriculture, and delivery services. For these missions to be safe and reliable—especially when drones fly beyond a pilot’s line of sight—they must always know their location accurately. Today, most drones depend on GPS, but GPS signals can be blocked by tall buildings, weakened indoors, or deliberately disrupted. This thesis explores how next-generation 5G cellular networks can help drones maintain accurate location information and operate more safely, even when GPS is unavailable. The first part of this work explains how recent wireless communication standards have added new features specifically designed for drones. These features support drone identification, tracking, safe communication with controllers, and coordination with air-traffic systems. We also highlight several gaps in today’s standards and identify opportunities where future improvements could make drone operations even more reliable. The second part of the thesis introduces the first 5G-enabled drone testbed built at Wireless@ VT. This platform allowed us to study how communication delays affect the ability of multiple drones to fly together as a coordinated group, or “swarm.” Our experiments show that a key factor in improving swarm responsiveness is the way 5G divides its radio channels. By increasing the spacing between these channels—known as the subcarrier spacing—the network can transmit information more quickly, reducing delay and enabling drones to react faster. This behavior closely aligns with the goals of future ultra-reliable, low-latency communication services. Finally, the thesis presents a new way for drones to choose flight paths that improve how accurately they can determine their location using 5G signals. By selecting routes that offer better geometry with respect to nearby cell towers, a drone can significantly reduce its positioning uncertainty without harming its communication performance. Together, these contributions show how 5G networks can enhance the safety, reliability, and autonomy of drone operations, particularly in situations where GPS alone is not enough."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/10919/141181"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["uncrewed aerial vehicles","localization","path planning","3GPP","UAV testbed"],"dc:title":["Management and Analysis of Localization Information in Uncrewed Aerial Systems"],"dc:type":["Thesis"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:33Z"}